Reaction of chitosan with genipin and its fluorogenic attributes for potential microcapsule membrane characterization
Bibliographic record
Abstract
This study investigates the fluorogenic characteristics of the chitosan-genipin reaction for applications in microencapsulation research. Results showed that the chitosan-genipin reaction generated a colored and fluorescent product, with optimal excitation and emission wavelengths at 369 and 470 nm, respectively. Furthermore, it was found that reaction conditions affected the fluorescence intensity of the product. Mixture at the ratio of 4:1 (chitosan: genipin by weight) fluoresced the most. It also fluoresced stronger if the reaction occurred at higher temperature, with the intensity of 10.4 x 10(5) CPS at 37 degrees C, 5.9 x 10(5) CPS at 20 degrees C, and 2.5 x 10(5) CPS at 4 degrees C. As well, the fluorescence of the mixture developed gradually over time, attaining the emission maxima of 2.9 x 10(5), 7.6 x 10(5), and 10.0 x 10(5) CPS in 1, 6, and 18 h, respectively. Chitosan-coated alginate microcapsules were prepared without prior labeling, to which subsequent genipin treatment was applied in order to examine the potential of using genipin in microcapsule characterization. Chitosan bound to the alginate beads interacted with genipin, from which the resultant fluorescent signals allowed for clear visualization of the chitosan coating under confocal laser scanning microscopy. The relative fluorescence intensity across the chitosan membrane was found to be considerably higher than the controls (175 vs. 50). The membrane thickness measured was 29.2 +/- 7.3 microm. These findings demonstrate a convenient and effective way of characterizing chitosan-based microcapsules using genipin as a fluorogenic marker, a technique that will be useful in microcapsule research and other biomedical applications.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".